Job description
Who Are We? At Hy. Prix, we're building supersonic payload delivery systems for autonomy. Things flying faster than the speed of sound - we are enabling them with cheap hardware. Replicating the capabilities of expensive conventional frontline systems - we are building micro missiles for mass manufacturability with unit economics in 5 digits.
Built for a war of attrition, build for the era of software defined warfare, built to cater to the front lines of battlefields - where no man should stand in the future. Learn more about us: https://hyprix.in About the role You will design and implement advanced control architectures for airborne supersonic bodies and coordinate with the rest of the GNC team.
Qualifications
Anyone with a Bachelor's, Master's, or PhD in Aerospace, Electrical or Mechanical Engineering (or a drop-out for all that matters) Experience: 3-5 years Location: On-site | Bengaluru Core Responsibilities Run high fidelity 6-DOF simulations and analyze aerodynamic characteristics while deriving linear models, operating points and transfer functions Design and implement various linear and nonlinear control architectures to achieve stability and high performance on supersonic flight systems Develop state estimation algorithms in highly constrained environments using both conventional and learning based methods.
Design and implement calibration techniques and noise filtering for sensors and actuators Support hardware implementation by porting your algorithms to embedded systems and verifying them in hardware-in-the-loop (HIL) simulations. Design guidance algorithms for maneuverable flight and swarm flight mechanics. Required Qualifications Strong conceptual foundations in calculus, flight dynamics, control theory and filters.
Experience with design and tuning of robust and optimal linear control methods such as PID, compensator design, LQR and LQG. Good understanding of nonlinear dynamics and stability including Jacobian linearisation, Lyapunov stability and Lyapunov based control methods (Sliding mode, Backstepping, Adaptive) Conceptual understanding of advanced control methods such as predictive control, H-infinity synthesis, stochastic control and neuro-fuzzy techniques Proficiency with computational tools such as MATLAB/Simulink and Python with emphasis on control systems and signal processing.
Experience with writing embedded C code and hardware implementation of control algorithms. Should you really join us? If you like learning, if you like figuring things out by yourself without others telling you how to do it - and thrive under work pressure to ship missiles - then this is for you. Join us to take ownership of your work.
We are a lean team - there is no one to micro-manage you and no one to guide you either. You have an end goal - which is based on a real product - and you need to get it done your own way. It's hard, and we all love it here.
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